Non-human identity governance is lagging behind cloud automation

At a glance

What this is: This is an independent analysis of non-human identities and the governance gap they create as machine-driven access becomes foundational to enterprise operations.

Why it matters: It matters because IAM, PAM, and IGA teams must govern service accounts, APIs, workloads, bots, and AI systems as first-class identities, not as residual technical artefacts.

By the numbers:

• Only 38% have automated certificate lifecycle management in place.
• 57% of organisations lack a complete inventory of their machine identities.
• 69% of organisations now have more machine identities than human ones.

👉 Read SecurEnds' article on non-human identity governance and access risk

Context

Non-human identities are the machine accounts, service identities, API credentials, workload identities, and automation tokens that let systems authenticate and act without a person present. The governance gap is that many IAM programmes still treat these identities as operational leftovers, even though they now carry the access paths that run cloud deployments, integrations, and background workflows.

For identity teams, the issue is not whether machine identities exist, but whether they are owned, scoped, reviewed, rotated, and monitored with the same rigour applied to human access. As cloud estates and AI-enabled workflows expand, the failure mode shifts from user access sprawl to hidden, persistent machine access across production systems.

Key questions

Q: How should security teams govern non-human identities at scale?

A: Start with discovery, ownership, and entitlement control. Security teams need a complete inventory of service accounts, API keys, tokens, certificates, and workload identities, then assign each one to a responsible owner. From there, enforce least privilege, rotate secrets on schedule, and review access regularly so machine identities do not become permanent hidden access paths.

Q: Why do non-human identities increase enterprise access risk?

A: They often operate continuously, hold elevated permissions, and use long-lived credentials that are harder to track than human access. That combination expands the blast radius of credential exposure, makes privilege creep easier to miss, and leaves dormant identities active long after the original business need has ended.

Q: What breaks when machine identities do not have clear ownership?

A: Without ownership, nobody can reliably approve access, validate necessity, rotate credentials, or retire the identity when the workload changes. The result is orphaned access, audit gaps, and a growing population of machine identities that remain active by default even when their business purpose is gone.

Q: How can organisations tell whether machine identity governance is working?

A: Look for a current inventory, named owners, routine entitlement reviews, credential rotation evidence, and a measurable drop in dormant or overprivileged identities. If those signals are missing, the programme is likely managing individual credentials but not governing the identity lifecycle end to end.

Technical breakdown

Why machine identities become persistent access paths

Machine identities differ from human accounts because they are built to run continuously, often across systems that never share a single administrative boundary. A service account, API key, or workload identity can authenticate thousands of times without a human session boundary, which makes its effective privilege window much longer than a user login. That persistence is useful for automation, but it also creates durable trust that is hard to observe, review, or retire once the original use case changes. In practice, the identity is often more stable than the workload it serves.

Practical implication: treat machine identities as continuously active privileges, not occasional logins, and govern them accordingly.

How hardcoded secrets and unrotated credentials turn into exposure

Hardcoded API keys, long-lived tokens, and unrotated certificates create a direct path from convenience to compromise. When secrets are embedded in code, scripts, or repositories, their exposure surface expands to every developer workflow and every downstream system that can read the artefact. Rotation reduces that risk only if organisations can locate every copy, dependency, and integration point tied to the credential. Without that inventory, a secret change can break operations or leave old credentials alive in shadow systems.

Practical implication: map every secret to its owning workload before rotation, or you will miss the credentials that matter most.

Why ownership and entitlement reviews are the real control plane

Ownership is the control that turns a machine identity from an anonymous asset into a governable access object. Entitlement reviews, logging, and monitoring all depend on someone being accountable for deciding whether the identity still needs its permissions. Without that owner, service accounts and automation credentials accumulate access by default, then remain active after projects end or integrations are retired. This is why machine identity governance is not just a discovery problem. It is an accountability problem that shows up as privilege creep, orphaned access, and audit failure.

Practical implication: require named ownership for every non-human identity before granting or renewing access.

NHI Mgmt Group analysis

Non-human identity governance is now an access governance problem, not a niche infrastructure concern. The article correctly frames service accounts, APIs, bots, workloads, and AI systems as identities that make decisions about access at machine speed. That changes the governance baseline: entitlement visibility, ownership, and review cadence matter because these identities can outlive the projects and teams that created them. Practitioners should treat machine identities as part of the core IAM estate, not an edge case.

Hardcoded credentials are not just weak secrets management. They are durable trust leaks. Once an API key or token is embedded in code or deployment artefacts, the credential gains a second life outside the intended operational boundary. That breaks the assumption that access is controlled only through the application runtime. The implication is that machine identity risk is often a lifecycle problem disguised as a secrets problem, because the real failure is unmanaged persistence.

Unknown ownership is the named failure mode behind most machine identity sprawl. The control gap is not simply missing inventory, but identities that cannot be assigned to a responsible party for review, renewal, or retirement. When no owner exists, least privilege cannot be enforced consistently and dormant access stays live by default. Practitioners should recognise orphaned machine identities as a governance defect with direct audit and exposure consequences.

Machine identity scale is already outgrowing human identity assumptions. The article’s point that machine identities now frequently outnumber people reflects a broader programme shift: human-centric access processes do not scale cleanly to automated estates. That does not mean human IAM becomes irrelevant. It means access governance must operate across both human and non-human estates with different telemetry, review methods, and lifecycle triggers. Practitioners need one governance model, not separate silos.

Automation expands business capability faster than governance maturity can absorb it. Cloud-native delivery, RPA, and AI workflows increase the number of identities that can act without direct human intervention, but most programmes still lack the central inventory and review discipline to keep pace. The result is structural overprovisioning, not isolated misconfiguration. Security teams should expect machine identity governance to become a board-level risk signal, especially where regulated data or production workloads are involved.

From our research:

• 57% of organisations lack a complete inventory of their machine identities, according to The Critical Gaps in Machine Identity Management report.
• 53% of organisations have experienced a security incident directly related to machine identity management failures.
• Inventory is only one part of the problem, so read Ultimate Guide to NHIs , Standards for the control model that turns discovery into governance.

What this signals

Machine identity programmes are entering a scale phase where manual control is no longer credible. With 69% of organisations now having more machine identities than human ones, the governance burden is shifting away from user-centric IAM process design and toward continuous machine identity lifecycle management. Teams that still depend on spreadsheet tracking and periodic clean-up will struggle to keep pace with automation growth.

Identity teams should expect secrets sprawl to become a recurring audit finding. The presence of hardcoded tokens, unrotated certificates, and orphaned service accounts means the operational risk is no longer limited to compromise. It now includes the inability to prove control, ownership, and timely retirement across the identity estate.

Ownership is the concept to sharpen next: a machine identity without accountable ownership is not an asset, it is unresolved access debt. That debt grows as cloud integration, RPA, and AI workflows multiply the number of identities that can act without a person in the loop, so programmes should align discovery with lifecycle enforcement.

For practitioners

• Build a complete machine identity inventory Continuously discover service accounts, API credentials, automation bots, workload identities, and certificates across cloud and hybrid environments, then map each identity to a named owner and system of record.
• Enforce least privilege at the identity level Review permissions for non-human identities against actual workload function, remove broad administrative access, and separate production access from build, test, and administrative workflows wherever possible.
• Rotate and retire secrets on an ownership schedule Tie token, key, and certificate rotation to explicit ownership, dependency mapping, and retirement dates so dormant or duplicated credentials do not persist after the original application or integration changes.
• Operationalise recurring entitlement reviews Use access reviews to identify orphaned service accounts, unused API credentials, and overprivileged workload identities, then require remediation evidence before the next certification cycle closes.

Key takeaways

• Non-human identities now represent a core access governance surface because they authenticate continuously, often with broader permissions than human users.
• The biggest machine identity risks are inventory gaps, hardcoded credentials, unrotated secrets, and orphaned ownership, not just poor visibility.
• Effective governance depends on discovery, accountability, least privilege, rotation, and recurring reviews working as one lifecycle process.

Key terms

• Non-Human Identity: A non-human identity is any digital identity used by software, infrastructure, or automation to authenticate and act without a person present. In practice, this includes service accounts, API keys, tokens, certificates, workload identities, bots, and AI-driven systems that need governed access.
• Machine Identity Governance: Machine identity governance is the discipline of discovering, owning, reviewing, and retiring non-human identities across their lifecycle. It combines inventory, entitlement control, secret management, and monitoring so automated access stays tied to a business purpose and does not accumulate unmanaged privilege.
• Secret Rotation: Secret rotation is the process of replacing credentials such as keys, tokens, passwords, or certificates on a controlled schedule. For machine identities, rotation only reduces risk when the organisation knows every place the secret is used, who owns it, and how to retire old copies safely.
• Orphaned Access: Orphaned access is permission that remains active after the identity, workload, or owner that justified it is gone. For non-human identities, it usually appears when projects end, integrations change, or service accounts are created without a durable accountability chain.

Deepen your knowledge

NHI governance, agentic AI identity, and machine identity lifecycle are core topics in our NHI Foundation Level course, the industry's only accredited NHI security programme. If you are responsible for identity security strategy or governance in your organisation, it is worth exploring.

This post draws on content published by SecurEnds: non-human identities explained and governed for modern enterprise environments. Read the original.